Integration of Spatial Probability and Size in Slope-Unit-Based Landslide Susceptibility Assessment: A Case Study.

Hengxing Lan,Langping Li

doi:10.3390/ijerph17218055

Abstract

Landslide spatial probability and size are two essential components of landslide susceptibility. However, in existing slope-unit-based landslide susceptibility assessment methods, landslide size has not been explicitly considered. This paper developed a novel slope-unit based approach for landslide susceptibility assessment that explicitly incorporates landslide size. This novel approach integrates the predicted occurrence probability (spatial probability) of landslides and predicted size (area) of potential landslides for a slope-unit to obtain a landslide susceptibility value for that slope-unit. The results of a case study showed that, from a quantitative point of view, integrating spatial probability and size in slope-unit-based landslide susceptibility assessment can bring remarkable increases of AUC (Area under the ROC curve) values. For slope-unit-based scenarios using the logistic regression method and the neural network method, the average increase of AUC brought by incorporating landslide size is up to 0.0627 and 0.0606, respectively. Slope-unit-based landslide susceptibility models incorporating landslide size had utilized the spatial extent information of historical landslides, which was dropped in models not incorporating landslide size, and therefore can make potential improvements. Nevertheless, additional case studies are still needed to further evaluate the applicability of the proposed approach.

Highlights

Landslide is a phenomenon in which a mass of rock, debris, or earth moves down a slope [1,2].Landslides can cause huge losses of life and economy; about 14% of total casualties from natural disasters are caused by landslides [3]
This paper presented a novel slope-unit-based approach for landslide susceptibility assessment that explicitly integrates landslide spatial probability and size
Previous slope-unit-based approaches only predict the occurrence probability of landslides by generating a “class prediction model”, while this novel approach predicts the size of landslides by generating a “size prediction model” and further multiplies the predicted occurrence probability and size of landslides to get a landslide susceptibility value for a slope-unit

Summary

Introduction

Landslide is a phenomenon in which a mass of rock, debris, or earth moves down a slope [1,2]. Landslides can cause huge losses of life and economy; about 14% of total casualties from natural disasters are caused by landslides [3]. Landslide risk assessment and mitigation are of great significance for human beings. Landslide susceptibility assessment is an essential step of landslide risk assessment [4], had been one of the major focuses of landslide studies [5,6,7]. China is badly affected by fatal landslides [8]. Major regions severely affected by landslides in China include the southwest mountainous area [9], southeast coastal area [10], and the loess plateau [11]

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Results

Conclusion